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Tag: Big Data Engineer
What exactly is data engineering? The process of planning and constructing infrastructures for the gathering, storage, and analysis of data is referred to as “data engineering.” This is a general area of application that may be found in practically every industry. The field of data engineering employs a significant number of data scientists. Data engineers … Continue reading The need for extensive data to make decisions more effectively and quickly
Data lineage isn’t new, but automation has finally made it accessible and scalable-to a certain extent. In the old days (way back in the mid-2010s), lineage happened through a lot of manual work. This involved identifying data assets, tracking them to their ingestion sources, documenting those sources, mapping the path of data as it moved … Continue reading Data Lineage is Broken – Here Are 5 Solutions To Fix ItData Lineage is Broken – Here Are 5 Solutions To Fix It
For data teams, bad data, broken data pipelines, stale dashboards, and 5 a.m. fire drills are par for the course, particularly as data workflows ingest more and more data from disparate sources. Drawing inspiration from software development, we call this phenomenon data downtime– but how can data teams proactively prevent bad data from striking in … Continue reading 5 Strategies For Stopping Bad Data In It’s Tracks
Data self-service, the ability for stakeholders in the organization to answer their own business questions with data, is a top initiative for nearly every data leader I’ve spoken to this year. It’s so foundational to creating a data-driven organization, that most of the questions surrounding it focus on the “when” rather than the “why.” /certifications/ … Continue reading Is “Self-Service” Data’s Biggest Lie?
Say it with me: bad data is inevitable. It doesn’t care about how proactive you are at writing dbt tests, how perfectly your data is modeled, or how robust your architecture is. The possibility of a major data incident (Null value? Errant schema change? Failed model?) that reverberates across the company is always lurking around … Continue reading You Can’t Out-Architect Bad Data
As analytics professionals, we deal in data: serving ad-hoc reports on a minute’s notice, pulling queries for executives, and generally forecasting company performance across a variety of metrics. But how can we be truly successful if we don’t measure our own performance, too? In this article, we discuss six important steps to setting goals for … Continue reading 6 Crucial Steps For Setting Your Data Team KPIs
/e20-065-dell-emc-advanced-analytics-specialist-for-data-scientists/ Nowadays, it seems like every data person falls into two camps: those who understand the data mesh and those who don’t. Rest assured: if you’re in either camp, you’re not alone! Rarely in recent memory has a topic taken the data world by storm, spawning a thriving community, hundreds of blog articles, and sighs … Continue reading Understanding the Data Mesh
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